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07/28/2023
RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control
We study how vision-language models trained on Internet-scale data can b...
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05/05/2023
Deep RL at Scale: Sorting Waste in Office Buildings with a Fleet of Mobile Manipulators
We describe a system for deep reinforcement learning of robotic manipula...
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12/13/2022
RT-1: Robotics Transformer for Real-World Control at Scale
By transferring knowledge from large, diverse, task-agnostic datasets, m...
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04/04/2022
Do As I Can, Not As I Say: Grounding Language in Robotic Affordances
Large language models can encode a wealth of semantic knowledge about th...
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10/19/2021
A Simple Approach to Continual Learning by Transferring Skill Parameters
In order to be effective general purpose machines in real world environm...
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06/24/2021
Towards Exploiting Geometry and Time for Fast Off-Distribution Adaptation in Multi-Task Robot Learning
We explore possible methods for multi-task transfer learning which seek ...
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04/15/2021
Actionable Models: Unsupervised Offline Reinforcement Learning of Robotic Skills
We consider the problem of learning useful robotic skills from previousl...
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04/21/2020
Efficient Adaptation for End-to-End Vision-Based Robotic Manipulation
One of the great promises of robot learning systems is that they will be...
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10/24/2019
Meta-World: A Benchmark and Evaluation for Multi-Task and Meta Reinforcement Learning
Meta-reinforcement learning algorithms can enable robots to acquire new ...
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10/04/2018
Zero-Shot Skill Composition and Simulation-to-Real Transfer by Learning Task Representations
Simulation-to-real transfer is an important strategy for making reinforc...
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09/29/2018
Auto-conditioned Recurrent Mixture Density Networks for Complex Trajectory Generation
Recent advancements in machine learning research have given rise to recu...
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09/26/2018